Today, Pluralsight released my 12th course. I’ve spent the last few months putting together a fun deep dive into three major database technologies from AWS: Amazon RDS (relational database), DynamoDB (NoSQL database), and Redshift (data warehouse). This 5+ hour course — Amazon Web Services Databases in Depth — explains when to use each, how to provision, how to configure for resilience and performance, and how to interact with each from applications and client tools. The modules include:

Getting Started. Here, we talk about the AWS database universe, how databases are priced, and what our (Node.js) sample application looks like.

Amazon RDS – Creating Instances, Loading Data. RDS supports SQL Server, PostgreSQL, Oracle, and MySQL, and this module explains the native capabilities and how to set up the service. We dig through the various storage options, how to secure access to the database, and how to create and load tables.

Amazon RDS – Lifecycle Activities. What do you do once your database is up and running? In this module we look at doing backup and restore, scaling databases up, setting up read-only database replicas, and setting up synchronous nodes in alternate availability zones.

Amazon DynamoDB – Creating and Querying. In this module, we talk about the various types of NoSQL databases, DynamoDB’s native capabilities, and how to set up a table. I dig into DynamoDB’s data model, automatic partitioning scheme, and critical considerations for designing tables (and primary keys). Then, we add and query some data.

Amazon DynamoDB – Tuning and Scaling. While DynamoDB takes care of a lot of things automatically, there are still operational items. In this module we talk about securing tables, the role of indexes, how to create and query global secondary indexes, and how to scale and monitor tables.

Amazon Redshift – Creating Clusters and Databases. Here we discuss the role of data warehouses, how Redshift is architected, how to create new clusters, how encryption works, and more. We go hands on with creating clusters and adding new database tables.

Amazon Redshift – Data Loading and Managing. A data warehouse is only useful if it has data in it! This module takes a look at the process for data loading, querying data, working with snapshots, resizing clusters, and using monitoring data.

Of course, you may ask why someone who works for CenturyLink – a competitor of AWS – would prepare a course on their product set. I’ve always enjoyed playing with a wide range of technologies from a diverse set of vendors. While satisfying my own technology curiosity, teaching courses like this also helps me position CenturyLink’s own products and have deep, meaningful conversations with our customers. Everybody wins.

I’m not sure what course will be next, but I welcome your feedback on this one, and hope you enjoy it!